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Four-Bar Path Synthesis for Variable Camber Wing Using Two Steps Approach
(2026-01-01)
Cortez, Spencer Troy P.
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Sleesongsom, Suwin
The variable camber wing (VCW) mechanism synthesis is a present research aim. The variable camber wing is a main track for development of morphing aircraft from the past to the present due to it seems the high lift device in a traditional modern aircraft, but the separate flow due to its slot can be suppressed with the continuous shape changing. With structural-based camber change, the mechanism design requires a new technique in synthesizing the variable camber mechanism, which expects to adapt its’ trailing edge. The deflection angle causes the VCW to generate an additional lift to the main body wing. The two-step approach is used in designing the new VCW mechanism which is crucial when it starts with aerodynamic analysis at different deflected angles and follow with VCW mechanism synthesis. The mechanism synthesis expects to minimize the error between actual mechanism motion and target trailing edge points. The task of this research is to include design constraints to have the possibility of the four-bar mechanism to work well, and be able to work and be placed inside of the trailing edge. The optimizers are selected to tackle the problem is a variation of teaching learning-based optimization. The results show the proposed method with two-step approach which can synthesize the variable camber wing mechanism and also meet with the design targets.
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A HEURISTIC ENHANCING ARTIFICIAL IMMUNE SYSTEM FOR THREE-DIMENSIONAL LOADING CAPACITATED VEHICLE ROUTING PROBLEM
(2025-06-08)
Thapatsuwan, Peeraya
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Thapatsuwan, Warattapop
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Kulworatit, Chaichana
This study addresses the Three-Dimensional Loading Capacitated Vehicle Routing Problem (3L-CVRP), a highly complex NP-hard problem that combines vehicle routing with spatially constrained three-dimensional bin packing. To tackle this challenge, we propose an enhanced Artificial Immune System (En-AIS) that integrates a novel local search heuristic called “Bring-i-to-j,” designed to improve routing feasibility and loading efficiency. The En-AIS algorithm is further refined through rigorous parameter tuning using a full factorial design and ANOVA analysis. Comparative experiments were conducted against conventional AIS and the Firefly Algorithm (FA) across 27 benchmark instances. Results demonstrate that En-AIS consistently outperforms both baseline methods in terms of solution quality, achieving an average improvement of 15–20% while maintaining competitive computational times. These findings highlight the algorithm’s robustness and its practical potential for application in logistics and supply chain optimization tasks involving joint routing and loading decisions.
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Ground structures-based topology optimization of a morphing wing using a metaheuristic algorithm
(2021-08-01)
Winyangkul, Seksan
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Wansaseub, Kittinan
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Sleesongsom, Suwin
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Panagant, Natee
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Kumar, Sumit
This paper presents multi-objective topology and sizing optimization of a morphing wing structure. The purpose of this paper is to design a new aircraft wing structure with a tapered shape for ribs, spars, and skins including a torsion beam for external actuating torques, which is antici-pated to modify the aeroelastic characteristic of the aircraft wing using multi-objective optimization. Two multi-objective topology optimization problems are proposed employing ground element structures with high-and low-grid resolutions. The design problem is to minimize mass, maximize difference of lift effectiveness, and maximize the buckling factor of an aircraft wing subject to aero-elastic and structural constraints including lift effectiveness, critical speed, and buckling factors. The design variables include aircraft wing structure dimensions and thickness distribution. The proposed optimization problems are solved by an efficient multi-objective metaheuristic algorithm while the results are compared and discussed. The Pareto optimal fronts obtained for all tests were compared based on a hypervolume metric. The objective function values for Case I and Case II at 10 selected optimal solutions exhibit a range of structural mass as 115.3216–411.6250 kg, 125.0137– 440.5869 kg, lift effectiveness as 1.0514–1.1451, 1.0834–1.1639 and bucking factor as 38.895–1133.1864 Hz, 158.1264–1844.4355 Hz, respectively. The best results reveal unconventional aircraft wing structures that can be manufactured using additive manufacturing. This research is expected to serve as a foundation for future research into multi-objective topology optimization of morphing wing structures based on the ground element framework.
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Reliability-based design of an aircraft wing using a fuzzy-based metaheuristic
(2021-07-02)
Winyangkul, Saksan
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Sleesongsom, Suwin
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Bureerat, Sujin
The purpose of this paper is to design aircraft wing using reliability-based design optimization concerned to fuzzy uncertainty variables. A possibilistic safety index-based design optimization (PSIBDO) with fuzzy uncertainties is proposed to overcome difficult tasks from the original probabilistic problem. The design problem is to minimize mass of a composite aircraft wing subject to aeroelastic and structural constraints through consideration of the material properties are the uncertainties. The design variables include aircraft wing structure dimensions. The reliability-based design approach is needed to alleviate such a problem. Due to the complexity of the aircraft wing structures design and aeroelastic analysis, nonprobability-based design is an alternative choice to increase computational efficiency in the design process. The optimum results show the efficiency of our proposed approach.
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Optimization of a High-Lift Mechanism Motion Generation Synthesis Using MHS
(2021-01-01)
Sleesongsom, Suwin
;
Bureerat, Sujin
The purpose of this paper is to synthesize a high-lift mechanism (HLM) of a transportation aircraft. In the past still lack in studying to synthesize of the HLM using a very recent technique. The device is an important mechanism to generate an addition lift to the wing of aircraft in take-off and landing condition. The crucial designing problem is to minimize the error between actual flap motion and target points. The optimum target points are positions and angles of flap at the take-off and landing condition. Designing constraints include the possibility of four-bar mechanism to work well, limiting position and includes workplace of mechanism. The optimizers are selected to tackle the problem is in a group of metaheuristics (MHs). The results show the propose method and MHs can synthesize the flap mechanism meet with the design targets.
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MULTIOBJECTIVE RELIABILITY-BASED DESIGN OF AN AIRCRAFT WING USING A FUZZY-BASED METAHEURISTIC
(2021-01-01)
Sleesongsom, Suwin
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Winyangkul, Saksan
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Bureerat, Sujin
This research presents a new multiobjective fuzzy-based metaheuristic (MOFBMH) for aircraft wing design, which considers the uncertain structural design based on a fuzzy set model. Usually, the objective of this kind of design problem is to minimize weight of the composite wing with failure possibility constraints rather than converting it to multiobjective optimization with a fuzzy variable vector for material properties and loading conditions. The proposed technique is established in the form of multiobjective optimization, which sets the possibilistic safety index (PSI) as an objective function along with structural weight. This technique can explore a possible reliability solution set in one optimization run, which is advantageous. The present technique is one of the posteriori-techniques that start with finding all solutions and choosing it later. Two design examples are used to demonstrate the present technique i.e.simple cantilever beam and composite aeroelastic wing design problems.The results show the proposed technique can explore all possible structures, which are more conservative, and realizable.
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A new selection operator to improve the performance of genetic algorithm for optimization problems
(2013-11-25)
Ritthipakdee, Amarita
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Thammano, Arit
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Premasathian, Nol
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Uyyanonvara, Bunyarit
Nature-inspired algorithms, such as Particle swarm optimization (PSO), Ant colony optimization (ACO), and Firefly algorithm, are well known for solving NP-hard optimization problems. They are capable of obtaining optimal solutions in a reasonable time. The algorithm presented in this paper is a combination of a firefly mating concept and genetic algorithm. Genetic algorithm is used as the core of the algorithm while a firefly mating concept is used to compose a new selection operator. The proposed algorithm is tested on four standard benchmark functions. Experimental results have confirmed that the proposed algorithm is not only computationally more efficient than both the original firefly algorithm and the genetic algorithm but also almost always ensure the optimal solutions. © 2013 IEEE.
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Water management simulation for electric current generation by Max-Min Ant system
(2009-12-01)
Roengruen, P.
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Ploysuk, B.
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Suesut, T.
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Gulphanich, S.
This paper is intended to purpose the development strategy in order to manage power generation in hydro power plant. The collecting data was used to investigate some factors that impact to power generation in hydro power plant and to integrate with Max-Min Ant system (MMAS) analysis which grouped in artificial intelligence. This method has been applied by the simulating ant food solution to properly compute the power generation which depends on time variant. Moreover, this method is computed based on the lowest producing cost. Finally, the analytical data has been simulated and tested on computer before launching to control the hydropower plant operation. © 2009 SICE.

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